Daniel Kifer
Professor of Computer Science & Engineering

-
W333 Westgate
University Park, PA - duk17@psu.edu
- 814-863-1187
Huck Affiliations
Links
Publication Tags
These publication tags are generated from the output of this researcher. Click any tag below to view other Huck researchers working on the same topic.
Learning Convolutional Neural Networks Travel Time Semantics Soil Moisture Neurons Big Data Moisture Trajectories Pixels Deep Learning Opinion Neural Networks Coding Crime Deep Neural Networks Science Baseline Prolongation Image Compression Landslide Hydrology Brain Trajectory AvailabilityMost Recent Publications
Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes
Prabhav Borate, Jacques Rivière, Chris Marone, Ankur Mali, Daniel Kifer, Parisa Shokouhi, 2023, Nature Communications
Differentiable modelling to unify machine learning and physical models for geosciences
Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew Farthing, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Yalan Song, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Binayak Mohanty, Tirthankar Roy, Chonggang Xu, Kathryn Lawson, 2023, Nature Reviews Earth and Environment on p. 552-567
Backpropagation-Free Deep Learning with Recursive Local Representation Alignment
Alexander G. Ororbia, Ankur Mali, Daniel Kifer, C. Lee Giles, 2023, on p. 9327-9335
Answering Private Linear Queries Adaptively using the Common Mechanism
Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer, 2023, Proceedings of the VLDB Endowment on p. 1883-1896
The neural coding framework for learning generative models
Alexander Ororbia, Daniel Kifer, 2022, Nature Communications
Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms
Zeyu Ding, Yuxin Wang, Wang Yuxin, Yingtai Xiao, Guanhong Wang, Danfeng Zhang, D Kifer, Daniel Kifer, 2022, VLDB Journal on p. 23-48
The 2020 census disclosure avoidance system TopDown algorithm.
John Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson Garfinkel, Micah Heineck, Christine Heiss, Robert Johns, Daniel Kifer, Philip Leclerc, Ashwin Machanavajjhala, Brett Moran, William Sexton, Matthew Spence, Pavel Zhuravlev, 2022, Harvard Data Science Review
Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting
Alexander G. Ororbia, C. Lee Giles, Ankur Mali, Daniel Kifer, 2022,
Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates
S. Nagendra, Daniel Kifer, S. Manjunatha, Benjamin Mirus, Kathryn Lawson, D Kifer, T. Pei, Daniel Kifer, W. Li, Kathryn Lawson, Te Pei, Srikanth Banagere Manjunatha, Benjamin Mirus, K. Lawson, H. Nguyen, Weixin Li Li, Hien Nguyen, Tong Qiu, S. Tran, T Qiu, Chaopeng Shen, C Shen, Sarah Tran, Chaopeng Shen, 2022, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing on p. 4349-4370
Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder
Ankur Mali, Alexander Ororbia, II, Alexander Ororbia, Daniel Kifer, Clyde Giles, 2022, CoRR on p. 471
Most-Cited Papers
Pufferfish: A framework for mathematical privacy definitions
Daniel Kifer, Ashwin Machanavajjhala, 2014, ACM Transactions on Database Systems
Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network
Kuai Fang, Chaopeng Shen, Daniel Kifer, Xiao Yang, 2017, Geophysical Research Letters on p. 11,030-11,039
HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community
Chaopeng Shen, Eric Laloy, Amin Elshorbagy, Adrian Albert, Jerad Bales, Fi John Chang, Sangram Ganguly, Kuo Lin Hsu, Daniel Kifer, Zheng Fang, Kuai Fang, Dongfeng Li, Xiaodong Li, Wen Ping Tsai, 2018, Hydrology and Earth System Sciences on p. 5639-5656
Learning to extract semantic structure from documents using multimodal fully convolutional neural networks
Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, Clyde Giles, 2017, on p. 4342–4351
Crime rate inference with big data
Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li, 2016, on p. 635-644
Learning to read irregular text with attention mechanisms
Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles, 2017, on p. 3280-3286
A Simple Baseline for Travel Time Estimation using Large-scale Trip Data
Hongjian Wang, Xianfeng Tang, Yu Hsuan Kuo, Daniel Kifer, Zhenhui Li, 2019, ACM Transactions on Intelligent Systems and Technology
Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection
Dafang He, Scott Cohen, Brian Price, Daniel Kifer, C. Lee Giles, 2017, on p. 254-261
Concentrated differentially private gradient descent with adaptive per-iteration privacy budget
Jaewoo Lee, Daniel Kifer, 2018, on p. 1656-1665
A neural temporal model for human motion prediction
Anand Gopalakrishnan, Ankur Mali, Dan Kifer, Lee Giles, Alexander G. Ororbia, 2019, on p. 12108-12117